high performance computing on graphics processing units: hgpu.org

Seismic trace interpolation is necessary for high-resolution imaging when the acquired data are not adequate or when some traces are missing. Projection-onto-convex-sets (POCS) interpolation can gradually recover missing traces with an iterative algorithm, but its computational cost in a 3D CPU-based implementation is too high for practical applications. We present a computing scheme to speed […]

This paper presents a parallel algorithm implemented on graphics processing units (GPUs) for rapidly evaluating spatial convolutions between the Helmholtz potential and a large-scale source distribution. The algorithm implements a non-uniform grid interpolation method (NGIM), which uses amplitude and phase compensation and spatial interpolation from a sparse grid to compute the field outside a source […]

In this paper, we explore the implementation of fault table generation on a Graphics Processing Unit (GPU). A fault table is essential for fault diagnosis and fault detection in VLSI testing and debug. Generating a fault table requires extensive fault simulation, with no fault dropping, and is extremely expensive from a computational standpoint. Fault simulation […]

This paper presents a novel optimizing compiler for general purpose computation on graphics processing units (GPGPU). It addresses two major challenges of developing high performance GPGPU programs: effective utilization of GPU memory hierarchy and judicious management of parallelism.

Geometry images resample meshes to represent them as texture for efficient GPU processing by forcing a regular parameterization that often incurs a large amount of distortion. Previous approaches broke the geometry image into multiple rectangular or irregular charts to reduce distortion, but complicated the automatic level of detail one gets from MIP-maps of the geometry […]

Computer-generated holography is a computationally intensive process particularly well suited to the architecture of graphics processing units (GPUs). This work investigates the performance improvements achievable through utilization of a GPU for optimization of holograms via simulated annealing. Two examples are given; accelerated training of an optical correlator to accept or reject inputs over sets of […]

We describe the porting of the Lattice Boltzmann component of MUPHY, a multi-physics/scale simulation software, to multiple graphics processing units using the Compute Unified Device Architecture. The novelty of this work is the development of ad hoc techniques for optimizing the indirect addressing that MUPHY uses for efficient simulations of irregular domains.

Among all the factors that determine the resolution of a 3D reconstruction by single particle electron cryo-microscopy (cryoEM), the number of particle images used in the dataset plays a major role. More images generally yield better resolution, assuming the imaged protein complex is conformationally and compositionally homogeneous. To facilitate processing of very large datasets, we […]

Recent advancements in cryo-electron microscopy (cryoEM) have made it technically possible to determine the three-dimensional (3D) structures of macromolecular complexes at atomic resolution. However, processing the large amount of data needed for atomic resolution reconstructions requires either accessing to very expensive computer clusters or waiting for weeks of continuous computation in a personal computer (PC). […]

Maximum-likelihood (ML) estimation has very desirable properties for reconstructing 3D volumes from noisy cryo-EM images of single macromolecular particles. Current implementations of ML estimation make use of the Expectation-Maximization (EM) algorithm or its variants. However, the EM algorithm is notoriously computation-intensive, as it involves integrals over all orientations and positions for each particle image. We […]

Functional magnetic resonance imaging allows non-invasive measurements of brain dynamics and has already been used for neurofeedback experiments, which relies on real time data processing. The limited computational resources that are typically available for this have hindered the use of connectivity analysis in this context. A basic, but already computationally demanding analysis method of neural […]

In this article, we look at early, recent, and state-of-the-art methods for registration of medical images using a range of high-performance computing (HPC) architectures including symmetric multiprocessing (SMP), massively multiprocessing (MMP), and architectures with distributed memory (DM), and nonuniform memory access (NUMA). The article is designed to be self-sufficient. We will take the time to […]